People often ask each other what kind of music they enjoy. I find it a tough question to answer, as I'm into all kinds of music, but it's hard to describe which common denominator can easily describe my preferences. Here's one way to describe musical tastes, using a tag cloud.
New: Generate your own tag cloud!
For about a year, I've been using the musical social networking services of Last.fm. The service tracks all music you play and generates interesting statistics about your musical preferences. You can track my preferences and statistics on my profile page. Last.fm then recommends all sorts of interesting music, based on the common musical knowledge of its 15 million user base, and their preferences. It's like a giant clustering algorithm trying to figure out who enjoys similar music, and work from that.
The following is a tag cloud, a list of keywords that Last.fm users adopt to describe my favorite artists. The tags are weighted by the play counts of the artists in my top 50 (in the week from 14 to 21 January 2007), and popularity of tags for these artists in Last.fm's database. The list was constructed using AudioScrobbler's web services, and a contraption of a script that glues it all together.
The tag cloud makes my musical preferences clear in an instant, the "electronic" keyword dominates the tag cloud. Besides a few strange entries (like "seen live"), I think the tag cloud renders a good overview of my musical preferences. Indeed, my preferences are all over the musical spectrum, with a tendency toward electronic music from the 90s. Too bad there's no "90s" tag in the cloud, as I think it's a common denominator of my preferences.
The following cloud is based on my top artists of the following week. There's a few small changes in my weekly preferences, mainly visible is the shift toward more music tagged with "trance." And hey, the "90s" tag is in my cloud!
The following cloud is based on MightyJay's profile, a friend of mine on Last.fm. As you can immediately observe, his musical preference is quite different from mine. We share a couple of tags, but the overlap is small.
Lastly, here's the tag cloud of another friend, with yet a different musical profile.
Last.fm uses artists, tracks, and albums to correlate music preferences and to find neighboring users (neighbors with respect to similar taste). According to Last.fm, user SintaxError is my closest current neighbor. The following tag cloud is created from this user's profile, and again my profile as a reference.
Note the similarities and small differences. Although we are considered neighbors, the clouds show that I have a broader preference to musical styles, where SintaxError has a few tags that I miss. If this user's preference is like mine, I should look for more music tagged with breakbeat, breaks, downtempo, funk, goa, grunge and hip-hop. Personally, I think that this mix of tags would be a great source of interesting music. From a statistical point of view, I would have to analyze more neighbors' data to find good recommendations for better exploration of available music.
The following cloud gives better insights into the differences among my cloud and my closest neighbor's, as in Figure 4. The difference cloud shows green tags if these are more expressed in my tag cloud than in SintaxError's, where red tags denotes music that he prefers more than me. The tag sizes are weighted by the absolute difference.
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Besides the hints (breaks, etc tags) I received from comparing our tag clouds before, I seem to have missed the biggest difference among our profiles. My neighbor's tag cloud has a bigger "electronica" tag than mine, and this shows in the difference tag cloud. I am, however, assuming that both "electronic" and "electronica" tags are used interspersed, and since "electronic" is the main tag in my tag cloud, I know that's indeed a tag that would fit in with my musical preferences. In comparison with SintaxError, I prefer rap metal (think Senser), psychedelic trance/techno and music with a political background. Note that these differences are however small with respect to the abundant similarities among our profiles.
The following difference cloud is between my cloud and MightyJay's, as in Figure 2. The differences in this tag cloud are quite different from the previous cloud (note that the colors have not been switched, although it appears so at first sight). The essential difference is that I listen to electronic music, and MightyJay listens to metal/rock (this result is not very surprising).
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Next, I have turned the process upside-down and generated a cloud of artists that share common tags. Based on the list of tags (breakbeat, breaks, downtempo, funk, goa, grunge, hip-hop and, electronica) that are not in my profile, but in SintaxError's tag cloud, I have generated a cloud of artists that share these tags, and are not in my list of all-time favorites. I look forward to tune in to some of these! I even listen to some of these, sporadically.
Since the scripts that analyze the data to generate these clouds is currently a big mess, I'll have to redo the code to make it available online, so you can generate your own musical tag clouds. So there's more to come, if I find the time!